meta-pytorch/skills

analyze-memory-snapshot

Analyze PyTorch CUDA memory snapshots from torch.cuda.memory._dump_snapshot(), torch.cuda.memory._snapshot(), or memory_viz artifacts. Use when the user wants to understand GPU memory usage, top allocation sites, deallocation timing, OOMs, allocator…

Quellsprache: Englisch

abi-stable

Migrate C++/CUDA PyTorch extension code to use the PyTorch stable ABI. Use when the user wants to make their project ABI stable, migrate to stable ABI, or use torch::stable APIs.

Quellsprache: Englisch

agents-are-coming

A dummy skill that announces the arrival of agents. Use when the user asks about agents, the agent revolution, or wants to hype up agents.

Quellsprache: Englisch

debug-graph-breaks

Debug and fix torch.compile graph breaks to prioritize and eliminate graph-breaks, and optionally achieve fullgraph compilation

Quellsprache: Englisch

profile-model

Analyze PyTorch profiler traces (.json/.json.gz). Use when the user wants to diagnose GPU performance issues, find slow kernels, identify idle time, analyze communication overhead, or debug training bottlenecks.

Quellsprache: Englisch